Papers by Keyword: VAR

Abstract: This article is devoted to examine the performance of power transformation in VAR and Bayesian VAR (BVAR) forecasts, in comparison with log-transformation. The effect of power transformation in multivariate time series model forecasts is still untouched in the literature. We examined the U.S. macroeconomic data from 1960 to 1987 and the Taiwan’s technology industrial production from 1990 to 2000. Our results showed that the power transformation provides outperforming forecasts in both VAR and BVAR models. Moreover, the non-informative prior BAVR with power transformation is the best predictive model and is recommendable to forecasting practice.

Abstract: This paper give a brief introduction for VAR model, through the analysis and comparison of the three classic VAR model: a historical simulation method, Monte Carlo simulation method, Delta-Normal method, combined with actual demand of the financial industry. A suitable system model named Delta-Normal method is summarized to develop the risk management system of the financial industry.

Abstract: Based on a real-world dataset, we developed multivariate time-series model to compare dynamic impacts of quality improvement, apology, compensation and communication on customer satisfaction, after a serious quality failure of mobile phone manufacturing system. The empirical results innovatively reveals that apology-based recovery efforts are the least effective in salvaging customer satisfaction of manufacturing system, with the shortest decay and lowest buildup intensity. In contrast, quality improvement is the most effective, with the highest buildup and longest decay but slowest buildup toward the peak impact point. Compensation has a moderate and stable impact over time. Communications’ impact on customer satisfaction of manufacturing system builds up the quickest, though with mild endurance and magnitude. These findings extend quality improvement literatures in the context of mobile phone manufacturing system

Abstract: The fuel ethanol industry has been in rapid development in recent years with the US as a leading force, which consumes large amount of corn. In order to assess the impact of corn-ethanol production on global corn price, a VAR model is used in this paper. By impulse responses analysis and variance decomposition analysis the direct impact of corn-ethanol production on global corn price and its relative importance compared with other external factors are proved. The results show that increasing amount of corn used for US ethanol production leads to rapid increases of global corn price when the corn production is steady. The proportion of corn used for ethanol production among total corn production in the US plays an important role in affecting global corn price among all external factors, and the significance of its impact will enhance in the long run. The fuel ethanol industry should turn to non-grain materials in the future to keep the global corn price steady and guarantee global food security, and it’s necessary for all fuel ethanol producers to take action.

Abstract: This paper analyzed the industrial structure deviation and the relationship between the industrial structure and economic growth with cointegration, and then established the VAR equation, which based on the data of the regional production index and industrial structure of Sichuan province from 1980 to 2009. The results showed that the industrial structure and economic growth of Sichuan exists the equilibrium relationship for a long time. The adjustment of industrial structure could change the mode of economic growth. This paper proposed that maintain and promote the development of tertiary industry were able to obtain the balance of economic growth and environmental protection in Sichuan Province.

Abstract: As uncertain processing time of some jobs may bring unpredicted deterioration of job shop scheduling performance, a measure of VaR is introduced into the job shop scheduling model, and a genetic algorithm combined with Monte Carlo simulation method is presented for solution. Lastly the numerical examples illustrate the efficiency of both the model and the algorithm.

Abstract: China has been in rapid economic growth and industrial structure reform for recent years, and oil, as a most important raw material for industrial production, its price fluctuations have direct impact on energy-intensive industries as well as non-energy-intensive industries and their associated industries’ overall demands. Under the price transmission mechanism, oil price volatility imposes significant influences on economic growth rate, price level, unemployment rate and monetary policy as well. This paper established VAR model among oil prices and economic indicators such as economic growth rate, price level, unemployment rate and monetary policy, and by data processing , stability test and cointegration test, we found that there existed long term stable cointegration relations among these sequences; through Granger Causality test we found that oil price volatility was the Granger cause of the fluctuations of economic growth rate, price level and monetary policy, and meanwhile, changes in economic growth rate is the Granger cause of that in price level. The result of our empirical study indicated that, oil price volatility has a profound influence on China’s economy, and thus, China should improve the establishment of the oil futures market to avoid risks of oil price volatility and secure long-term stability of its economic growth.

Abstract: Processing trade has gradually replaced the general trade, becoming China’s main trade pattern. Then, what’s the relationship between FDI and processing trade This paper, based on VAR model, by employing Granger causality test approach, impulse response function and variance decomposition, gives an empirical analysis and test of the dynamic correlation between FDI and processing trade. The empirical result denotes that there exists bilateral Granger causality relationship between FDI and processing trade. For a short period, the impact of FDI on the responsiveness of processing trade is more intense. The impact of processing trade on the responsiveness of FDI is also more intense and the volatility of fluctuations is larger; for a long period, there exists a long-run stable relationship between FDI and processing trade.

Abstract: With the data from 1980 to 2009, this paper gave an empirical analysis on the relation of transport development and economic growth by VAR model. Research shows that since the 30 years’ reform and opening up policy of China, the transportation and economic development have got a long-term positive mutually relationship, and make a positive interactive development state.

Abstract: Mean-variance model, value at risk and Conditional Value at Risk are three chief methods to measure financial risk recently. The demonstrative research shows that three optional questions are equivalence when the security rates have a multivariate normal distribution and the given confidence level is more than a special value. Applications to real data provide empirical support to this methodology. This result has provided new methods for us about further research of risk portfolios.